{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "(Un)conditional image generation with ImageGPT.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyOfQNn0uKLH1Qx0wbDNwap4",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/NielsRogge/Transformers-Tutorials/blob/master/ImageGPT/(Un)conditional_image_generation_with_ImageGPT.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hK6H7kLa0-iq"
      },
      "source": [
        "## Setting-up environment\n",
        "\n",
        "We first install HuggingFace Transformers."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "in7LYqdM06hM",
        "outputId": "816d1f86-4397-4498-82b7-2f6b20a9a21e"
      },
      "source": [
        "!pip install -q git+https://github.com/huggingface/transformers.git"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
            "  Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
            "    Preparing wheel metadata ... \u001b[?25l\u001b[?25hdone\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "IM5TZqwMlvth"
      },
      "source": [
        "## Unconditional image generation\n",
        "\n",
        "Next, we initialize the feature extractor and model, and put the model on the GPU."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "C7FWg9qyC__x",
        "outputId": "24762332-2d19-4760-a03f-9e29904be2ee"
      },
      "source": [
        "from transformers import ImageGPTFeatureExtractor, ImageGPTForCausalImageModeling\n",
        "import numpy as np\n",
        "import torch\n",
        "\n",
        "feature_extractor = ImageGPTFeatureExtractor.from_pretrained('openai/imagegpt-medium')\n",
        "model = ImageGPTForCausalImageModeling.from_pretrained('openai/imagegpt-medium')\n",
        "\n",
        "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
        "\n",
        "model.to(device)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "ImageGPTForCausalLM(\n",
              "  (transformer): ImageGPTModel(\n",
              "    (wte): Embedding(513, 1024)\n",
              "    (wpe): Embedding(1024, 1024)\n",
              "    (drop): Dropout(p=0.1, inplace=False)\n",
              "    (h): ModuleList(\n",
              "      (0): ImageGPTBlock(\n",
              "        (ln_1): ImageGPTLayerNorm()\n",
              "        (attn): ImageGPTAttention(\n",
              "          (c_attn): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (attn_dropout): Dropout(p=0.1, inplace=False)\n",
              "          (resid_dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "        (ln_2): ImageGPTLayerNorm()\n",
              "        (mlp): ImageGPTMLP(\n",
              "          (c_fc): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (1): ImageGPTBlock(\n",
              "        (ln_1): ImageGPTLayerNorm()\n",
              "        (attn): ImageGPTAttention(\n",
              "          (c_attn): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (attn_dropout): Dropout(p=0.1, inplace=False)\n",
              "          (resid_dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "        (ln_2): ImageGPTLayerNorm()\n",
              "        (mlp): ImageGPTMLP(\n",
              "          (c_fc): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (2): ImageGPTBlock(\n",
              "        (ln_1): ImageGPTLayerNorm()\n",
              "        (attn): ImageGPTAttention(\n",
              "          (c_attn): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (attn_dropout): Dropout(p=0.1, inplace=False)\n",
              "          (resid_dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "        (ln_2): ImageGPTLayerNorm()\n",
              "        (mlp): ImageGPTMLP(\n",
              "          (c_fc): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (3): ImageGPTBlock(\n",
              "        (ln_1): ImageGPTLayerNorm()\n",
              "        (attn): ImageGPTAttention(\n",
              "          (c_attn): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (attn_dropout): Dropout(p=0.1, inplace=False)\n",
              "          (resid_dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "        (ln_2): ImageGPTLayerNorm()\n",
              "        (mlp): ImageGPTMLP(\n",
              "          (c_fc): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (4): ImageGPTBlock(\n",
              "        (ln_1): ImageGPTLayerNorm()\n",
              "        (attn): ImageGPTAttention(\n",
              "          (c_attn): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (attn_dropout): Dropout(p=0.1, inplace=False)\n",
              "          (resid_dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "        (ln_2): ImageGPTLayerNorm()\n",
              "        (mlp): ImageGPTMLP(\n",
              "          (c_fc): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (5): ImageGPTBlock(\n",
              "        (ln_1): ImageGPTLayerNorm()\n",
              "        (attn): ImageGPTAttention(\n",
              "          (c_attn): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (attn_dropout): Dropout(p=0.1, inplace=False)\n",
              "          (resid_dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "        (ln_2): ImageGPTLayerNorm()\n",
              "        (mlp): ImageGPTMLP(\n",
              "          (c_fc): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (6): ImageGPTBlock(\n",
              "        (ln_1): ImageGPTLayerNorm()\n",
              "        (attn): ImageGPTAttention(\n",
              "          (c_attn): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (attn_dropout): Dropout(p=0.1, inplace=False)\n",
              "          (resid_dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "        (ln_2): ImageGPTLayerNorm()\n",
              "        (mlp): ImageGPTMLP(\n",
              "          (c_fc): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (7): ImageGPTBlock(\n",
              "        (ln_1): ImageGPTLayerNorm()\n",
              "        (attn): ImageGPTAttention(\n",
              "          (c_attn): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (attn_dropout): Dropout(p=0.1, inplace=False)\n",
              "          (resid_dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "        (ln_2): ImageGPTLayerNorm()\n",
              "        (mlp): ImageGPTMLP(\n",
              "          (c_fc): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (8): ImageGPTBlock(\n",
              "        (ln_1): ImageGPTLayerNorm()\n",
              "        (attn): ImageGPTAttention(\n",
              "          (c_attn): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (attn_dropout): Dropout(p=0.1, inplace=False)\n",
              "          (resid_dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "        (ln_2): ImageGPTLayerNorm()\n",
              "        (mlp): ImageGPTMLP(\n",
              "          (c_fc): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (9): ImageGPTBlock(\n",
              "        (ln_1): ImageGPTLayerNorm()\n",
              "        (attn): ImageGPTAttention(\n",
              "          (c_attn): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (attn_dropout): Dropout(p=0.1, inplace=False)\n",
              "          (resid_dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "        (ln_2): ImageGPTLayerNorm()\n",
              "        (mlp): ImageGPTMLP(\n",
              "          (c_fc): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (10): ImageGPTBlock(\n",
              "        (ln_1): ImageGPTLayerNorm()\n",
              "        (attn): ImageGPTAttention(\n",
              "          (c_attn): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (attn_dropout): Dropout(p=0.1, inplace=False)\n",
              "          (resid_dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "        (ln_2): ImageGPTLayerNorm()\n",
              "        (mlp): ImageGPTMLP(\n",
              "          (c_fc): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (11): ImageGPTBlock(\n",
              "        (ln_1): ImageGPTLayerNorm()\n",
              "        (attn): ImageGPTAttention(\n",
              "          (c_attn): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (attn_dropout): Dropout(p=0.1, inplace=False)\n",
              "          (resid_dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "        (ln_2): ImageGPTLayerNorm()\n",
              "        (mlp): ImageGPTMLP(\n",
              "          (c_fc): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (12): ImageGPTBlock(\n",
              "        (ln_1): ImageGPTLayerNorm()\n",
              "        (attn): ImageGPTAttention(\n",
              "          (c_attn): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (attn_dropout): Dropout(p=0.1, inplace=False)\n",
              "          (resid_dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "        (ln_2): ImageGPTLayerNorm()\n",
              "        (mlp): ImageGPTMLP(\n",
              "          (c_fc): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (13): ImageGPTBlock(\n",
              "        (ln_1): ImageGPTLayerNorm()\n",
              "        (attn): ImageGPTAttention(\n",
              "          (c_attn): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (attn_dropout): Dropout(p=0.1, inplace=False)\n",
              "          (resid_dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "        (ln_2): ImageGPTLayerNorm()\n",
              "        (mlp): ImageGPTMLP(\n",
              "          (c_fc): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (14): ImageGPTBlock(\n",
              "        (ln_1): ImageGPTLayerNorm()\n",
              "        (attn): ImageGPTAttention(\n",
              "          (c_attn): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (attn_dropout): Dropout(p=0.1, inplace=False)\n",
              "          (resid_dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "        (ln_2): ImageGPTLayerNorm()\n",
              "        (mlp): ImageGPTMLP(\n",
              "          (c_fc): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (15): ImageGPTBlock(\n",
              "        (ln_1): ImageGPTLayerNorm()\n",
              "        (attn): ImageGPTAttention(\n",
              "          (c_attn): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (attn_dropout): Dropout(p=0.1, inplace=False)\n",
              "          (resid_dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "        (ln_2): ImageGPTLayerNorm()\n",
              "        (mlp): ImageGPTMLP(\n",
              "          (c_fc): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (16): ImageGPTBlock(\n",
              "        (ln_1): ImageGPTLayerNorm()\n",
              "        (attn): ImageGPTAttention(\n",
              "          (c_attn): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (attn_dropout): Dropout(p=0.1, inplace=False)\n",
              "          (resid_dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "        (ln_2): ImageGPTLayerNorm()\n",
              "        (mlp): ImageGPTMLP(\n",
              "          (c_fc): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (17): ImageGPTBlock(\n",
              "        (ln_1): ImageGPTLayerNorm()\n",
              "        (attn): ImageGPTAttention(\n",
              "          (c_attn): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (attn_dropout): Dropout(p=0.1, inplace=False)\n",
              "          (resid_dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "        (ln_2): ImageGPTLayerNorm()\n",
              "        (mlp): ImageGPTMLP(\n",
              "          (c_fc): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (18): ImageGPTBlock(\n",
              "        (ln_1): ImageGPTLayerNorm()\n",
              "        (attn): ImageGPTAttention(\n",
              "          (c_attn): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (attn_dropout): Dropout(p=0.1, inplace=False)\n",
              "          (resid_dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "        (ln_2): ImageGPTLayerNorm()\n",
              "        (mlp): ImageGPTMLP(\n",
              "          (c_fc): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (19): ImageGPTBlock(\n",
              "        (ln_1): ImageGPTLayerNorm()\n",
              "        (attn): ImageGPTAttention(\n",
              "          (c_attn): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (attn_dropout): Dropout(p=0.1, inplace=False)\n",
              "          (resid_dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "        (ln_2): ImageGPTLayerNorm()\n",
              "        (mlp): ImageGPTMLP(\n",
              "          (c_fc): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (20): ImageGPTBlock(\n",
              "        (ln_1): ImageGPTLayerNorm()\n",
              "        (attn): ImageGPTAttention(\n",
              "          (c_attn): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (attn_dropout): Dropout(p=0.1, inplace=False)\n",
              "          (resid_dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "        (ln_2): ImageGPTLayerNorm()\n",
              "        (mlp): ImageGPTMLP(\n",
              "          (c_fc): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (21): ImageGPTBlock(\n",
              "        (ln_1): ImageGPTLayerNorm()\n",
              "        (attn): ImageGPTAttention(\n",
              "          (c_attn): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (attn_dropout): Dropout(p=0.1, inplace=False)\n",
              "          (resid_dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "        (ln_2): ImageGPTLayerNorm()\n",
              "        (mlp): ImageGPTMLP(\n",
              "          (c_fc): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (22): ImageGPTBlock(\n",
              "        (ln_1): ImageGPTLayerNorm()\n",
              "        (attn): ImageGPTAttention(\n",
              "          (c_attn): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (attn_dropout): Dropout(p=0.1, inplace=False)\n",
              "          (resid_dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "        (ln_2): ImageGPTLayerNorm()\n",
              "        (mlp): ImageGPTMLP(\n",
              "          (c_fc): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (23): ImageGPTBlock(\n",
              "        (ln_1): ImageGPTLayerNorm()\n",
              "        (attn): ImageGPTAttention(\n",
              "          (c_attn): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (attn_dropout): Dropout(p=0.1, inplace=False)\n",
              "          (resid_dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "        (ln_2): ImageGPTLayerNorm()\n",
              "        (mlp): ImageGPTMLP(\n",
              "          (c_fc): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (24): ImageGPTBlock(\n",
              "        (ln_1): ImageGPTLayerNorm()\n",
              "        (attn): ImageGPTAttention(\n",
              "          (c_attn): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (attn_dropout): Dropout(p=0.1, inplace=False)\n",
              "          (resid_dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "        (ln_2): ImageGPTLayerNorm()\n",
              "        (mlp): ImageGPTMLP(\n",
              "          (c_fc): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (25): ImageGPTBlock(\n",
              "        (ln_1): ImageGPTLayerNorm()\n",
              "        (attn): ImageGPTAttention(\n",
              "          (c_attn): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (attn_dropout): Dropout(p=0.1, inplace=False)\n",
              "          (resid_dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "        (ln_2): ImageGPTLayerNorm()\n",
              "        (mlp): ImageGPTMLP(\n",
              "          (c_fc): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (26): ImageGPTBlock(\n",
              "        (ln_1): ImageGPTLayerNorm()\n",
              "        (attn): ImageGPTAttention(\n",
              "          (c_attn): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (attn_dropout): Dropout(p=0.1, inplace=False)\n",
              "          (resid_dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "        (ln_2): ImageGPTLayerNorm()\n",
              "        (mlp): ImageGPTMLP(\n",
              "          (c_fc): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (27): ImageGPTBlock(\n",
              "        (ln_1): ImageGPTLayerNorm()\n",
              "        (attn): ImageGPTAttention(\n",
              "          (c_attn): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (attn_dropout): Dropout(p=0.1, inplace=False)\n",
              "          (resid_dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "        (ln_2): ImageGPTLayerNorm()\n",
              "        (mlp): ImageGPTMLP(\n",
              "          (c_fc): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (28): ImageGPTBlock(\n",
              "        (ln_1): ImageGPTLayerNorm()\n",
              "        (attn): ImageGPTAttention(\n",
              "          (c_attn): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (attn_dropout): Dropout(p=0.1, inplace=False)\n",
              "          (resid_dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "        (ln_2): ImageGPTLayerNorm()\n",
              "        (mlp): ImageGPTMLP(\n",
              "          (c_fc): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (29): ImageGPTBlock(\n",
              "        (ln_1): ImageGPTLayerNorm()\n",
              "        (attn): ImageGPTAttention(\n",
              "          (c_attn): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (attn_dropout): Dropout(p=0.1, inplace=False)\n",
              "          (resid_dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "        (ln_2): ImageGPTLayerNorm()\n",
              "        (mlp): ImageGPTMLP(\n",
              "          (c_fc): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (30): ImageGPTBlock(\n",
              "        (ln_1): ImageGPTLayerNorm()\n",
              "        (attn): ImageGPTAttention(\n",
              "          (c_attn): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (attn_dropout): Dropout(p=0.1, inplace=False)\n",
              "          (resid_dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "        (ln_2): ImageGPTLayerNorm()\n",
              "        (mlp): ImageGPTMLP(\n",
              "          (c_fc): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (31): ImageGPTBlock(\n",
              "        (ln_1): ImageGPTLayerNorm()\n",
              "        (attn): ImageGPTAttention(\n",
              "          (c_attn): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (attn_dropout): Dropout(p=0.1, inplace=False)\n",
              "          (resid_dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "        (ln_2): ImageGPTLayerNorm()\n",
              "        (mlp): ImageGPTMLP(\n",
              "          (c_fc): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (32): ImageGPTBlock(\n",
              "        (ln_1): ImageGPTLayerNorm()\n",
              "        (attn): ImageGPTAttention(\n",
              "          (c_attn): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (attn_dropout): Dropout(p=0.1, inplace=False)\n",
              "          (resid_dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "        (ln_2): ImageGPTLayerNorm()\n",
              "        (mlp): ImageGPTMLP(\n",
              "          (c_fc): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (33): ImageGPTBlock(\n",
              "        (ln_1): ImageGPTLayerNorm()\n",
              "        (attn): ImageGPTAttention(\n",
              "          (c_attn): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (attn_dropout): Dropout(p=0.1, inplace=False)\n",
              "          (resid_dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "        (ln_2): ImageGPTLayerNorm()\n",
              "        (mlp): ImageGPTMLP(\n",
              "          (c_fc): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (34): ImageGPTBlock(\n",
              "        (ln_1): ImageGPTLayerNorm()\n",
              "        (attn): ImageGPTAttention(\n",
              "          (c_attn): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (attn_dropout): Dropout(p=0.1, inplace=False)\n",
              "          (resid_dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "        (ln_2): ImageGPTLayerNorm()\n",
              "        (mlp): ImageGPTMLP(\n",
              "          (c_fc): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (35): ImageGPTBlock(\n",
              "        (ln_1): ImageGPTLayerNorm()\n",
              "        (attn): ImageGPTAttention(\n",
              "          (c_attn): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (attn_dropout): Dropout(p=0.1, inplace=False)\n",
              "          (resid_dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "        (ln_2): ImageGPTLayerNorm()\n",
              "        (mlp): ImageGPTMLP(\n",
              "          (c_fc): Conv1D()\n",
              "          (c_proj): Conv1D()\n",
              "          (dropout): Dropout(p=0.1, inplace=False)\n",
              "        )\n",
              "      )\n",
              "    )\n",
              "    (ln_f): ImageGPTLayerNorm()\n",
              "  )\n",
              "  (lm_head): Linear(in_features=1024, out_features=512, bias=False)\n",
              ")"
            ]
          },
          "metadata": {},
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AkSDHhdE0hQB"
      },
      "source": [
        "Here we only feed the start of sequence (SOS) special token to the model, and let it generate 32x32 = 1024 pixel values using the `generate()` method. Each pixel value is one of 512 possible color clusters."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lM610-VPyL-m",
        "outputId": "539b799f-9f3b-42c2-a793-68e53db29755"
      },
      "source": [
        "# unconditional generation of 8 images\n",
        "batch_size = 8\n",
        "context = torch.full((batch_size, 1), model.config.vocab_size - 1) #initialize with SOS token (with ID 512)\n",
        "context = torch.tensor(context).to(device)\n",
        "output = model.generate(input_ids=context, max_length=model.config.n_positions + 1, temperature=1.0, do_sample=True, top_k=40)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:4: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).\n",
            "  after removing the cwd from sys.path.\n",
            "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 205
        },
        "id": "nZmJ3KfBQApd",
        "outputId": "6ae40da7-bea2-4a45-cb5c-517ddbab4737"
      },
      "source": [
        "#visualize samples with Image-GPT color palette.\n",
        "%matplotlib inline\n",
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "\n",
        "clusters = feature_extractor.clusters\n",
        "n_px = feature_extractor.size\n",
        "\n",
        "samples = output[:,1:].cpu().detach().numpy()\n",
        "samples_img = [np.reshape(np.rint(127.5 * (clusters[s] + 1.0)), [32, 32, 3]).astype(np.uint8) for s in samples] # convert color cluster tokens back to pixels\n",
        "f, axes = plt.subplots(1, batch_size, dpi=300)\n",
        "\n",
        "for img, ax in zip(samples_img, axes):\n",
        "    ax.axis('off')\n",
        "    ax.imshow(img)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 1800x1200 with 8 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "u7xe3DCnXKG9"
      },
      "source": [
        "# Tokenize Cropped Images for Image Completion\n",
        "\n",
        "Given the upper half part of an image, it's interesting to see how ImageGPT would complete it. \n",
        "\n",
        "Let's check 8 completions for a given image. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 477
        },
        "id": "JzJ0LvQSmVrp",
        "outputId": "063600ad-0bbc-4b55-ceb7-1e5d18b9a9aa"
      },
      "source": [
        "import requests\n",
        "from PIL import Image\n",
        "\n",
        "url = 'https://assetsnffrgf-a.akamaihd.net/assets/m/502013285/univ/art/502013285_univ_sqr_xl.jpg'\n",
        "url = \"https://avatars.githubusercontent.com/u/326577?v=4\"\n",
        "image = Image.open(requests.get(url, stream=True).raw).convert(\"RGB\")\n",
        "image"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<PIL.Image.Image image mode=RGB size=460x460 at 0x7F87EB5B0290>"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1A5s9QKtOO-A"
      },
      "source": [
        "We prepare the images using ImageGPTFeatureExtractor, which will resize each image to 32x32x3, normalize it and then apply color clustering. Finally, it will flatten the pixel values out to a long list of 32x32 = 1024 values. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nyyhNIqOml9s",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "83f9d91d-8235-4894-d3d9-25de9cf474f2"
      },
      "source": [
        "encoding = feature_extractor([image for _ in range(8)], return_tensors=\"pt\")\n",
        "print(encoding.keys())"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "dict_keys(['pixel_values'])\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wMJZjyqw7_ab",
        "outputId": "55207ddc-e767-4b40-d89b-aa0e6097ce12"
      },
      "source": [
        "encoding.pixel_values.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "torch.Size([8, 1024])"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xU4jj3JyOcOw"
      },
      "source": [
        "Next, we only keep the first 512 tokens (pixel values)."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0f4DjAxAmoik"
      },
      "source": [
        "samples = encoding.pixel_values.numpy()\n",
        "n_px_crop = 16\n",
        "# crop top n_px_crop rows. These will be the conditioning tokens\n",
        "primers = samples[:,:n_px_crop*n_px] "
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "__WiNCQ2O64Q",
        "outputId": "6d5444a3-906b-4cad-952e-45fd408fd94a"
      },
      "source": [
        "print(primers.shape)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(8, 512)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sG1UEfkiPCT-"
      },
      "source": [
        "We can visualize both the original (lower-resolution and color-clustered) images and the cropped ones:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SggQqpPaXKHT",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 327
        },
        "outputId": "eac92835-5e68-4d64-e958-f76055054dc0"
      },
      "source": [
        "#visualize samples and crops with Image-GPT color palette. Should look similar to original resized images\n",
        "samples_img = [np.reshape(np.rint(127.5 * (clusters[s] + 1.0)), [n_px, n_px, 3]).astype(np.uint8) for s in samples] # convert color clusters back to pixels\n",
        "primers_img = [np.reshape(np.rint(127.5 * (clusters[s] + 1.0)), [n_px_crop,n_px, 3]).astype(np.uint8) for s in primers] # convert color clusters back to pixels\n",
        "\n",
        "f, axes = plt.subplots(1, batch_size, dpi=300)\n",
        "for img,ax in zip(samples_img, axes):\n",
        "    ax.axis('off')\n",
        "    ax.imshow(img)\n",
        "\n",
        "f, axes2 = plt.subplots(1, batch_size, dpi=300)\n",
        "for img,ax in zip(primers_img, axes2):\n",
        "    ax.axis('off')\n",
        "    ax.imshow(img)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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88hoAAAAAgHAMrwEAAAAACMfwGgAAAACAcAyvAQAAAAAIJ/QXNvbmm729ne1vKudH9788jbfzTIbD3eyuybL59z+sLrwfbA6yZ/7wne9ld68tLlfOl5avZM9s7vWzuye1u9uffJE988O3fje7W26wSP5gsD/yme8CHeu4C3Ss4y7QsY67QMc67gId67grtKzlLtCxjqPzyWsAAAAAAMIxvAYAAAAAIBzDawAAAAAAwjG8BgAAAAAgnNBf2NjU5uZ65Tzor2fP7A0PCz/5sHa+kT2xcnn0ovfF+fnsLl8ZX1gkX/i5ul8+yBfgb53fzu5ee6H63nuze9kz53sL2V19afz+4/xvd+du/j7/4K1blfOFudH/ltJzpcXypS8L2Ns/aPT6baZjHXeBjnXcBTrWcRfoWMddoGMdd4WWtdwFOtbxtPjkNQAAAAAA4RheAwAAAAAQjuE1AAAAAADhtG7ndWn/yv37G5XzTj/fejNzodlemLr6XpqUUhrWzqUdOyWzs9UdPrv7+c6Z0g6fujtflH5jdYfQ3rBXeCb/t5R28dR9s72Z3d27v1w533phdeTrpFTes/NdpGMdd4GOddwFOtZxF+hYx12gYx13hZa13AU61nEkPnkNAAAAAEA4htcAAAAAAIRjeA0AAAAAQDiG1wAAAAAAhBP6CxtLC+IHhaXjO/2ts3g7of3m03yxe119aX1KKQ2Ho1felxbnP3i4Xjn/zupK9szyxaXsbtyl8b35aqqlNqLScXM6jkvHzek4Lh03p+O4dNycjuPScXM6jk3LzWk5Lh03p+Pp8MlrAAAAAADCMbwGAAAAACAcw2sAAAAAAMIxvAYAAAAAIJzQX9hYMhzsZXe726MXn5+1xfn5kc/s7ucL1Ot3TV7nedQXyTdZIl967suNfHF/aWk8T+l4snQ8HTqeLB1Ph44nS8fToePJ0vF06HiydDw9Wp4sLU+HjidLx8/HJ68BAAAAAAjH8BoAAAAAgHAMrwEAAAAACKd1O6+3H+9kd4fDfBdP9sxBvuNm56C6c2amv53/vrSc3a30qufSrprS9pr6Dp3STp3SLp4m6q817uuUbO8dZXfLqV85b32d/+0OXpjce+gaHZfpuF10XKbjdtFxmY7bRcdlOm4XHZfpuH20XKbldtFxmY6nwyevAQAAAAAIx/AaAAAAAIBwDK8BAAAAAAjH8BoAAAAAgHBa94WNw4N8Qfze8LBynrmQL2Mv6R3Vl5rnC+J7F/LF5wv92cr5YOVS9syNy/l7WL64NPI93f+yei4tfy8tm5+U2dnF7G7lcv7cy9evVM7zvZnsmeH+Vv768ytjva+9/YOxfi4qHeu4C3Ss4y7QsY67QMc67gId67grtKzlLtCxjiPxyWsAAAAAAMIxvAYAAAAAIBzDawAAAAAAwjG8BgAAAAAgnKl9YeNgkC9Dn5sbvQx99kLvNN5OSimlizP5Qvof3nw5u3vjperC9Ffffid7ZvXmana32Ls48j3847/+R+X8T7/6JHtm3EXyw+FudldfEl96nb/86XvZ3dtXC5vkazb6/ezuw7WHlfN2y///iY7LdNwuOi7TcbvouEzH7aLjMh23i47LdNw+Wi7TcrvouEzH7dLudw8AAAAAQCcZXgMAAAAAEI7hNQAAAAAA4Uxt5/W45nszI585PMj30gyGw+xuf6u6F+bWxe9lzxxtf1P4DVcKd1VXewfZ3eXD0TuDfvJ7r1TO73+4lj1T2rtTV9qf801h704TNxcLO30uLVSOpX9vephfXVqcrZy3dw/Hek9tp2Mdd4GOddwFOtZxF+hYx12gYx13hZa13AU61nEkPnkNAAAAAEA4htcAAAAAAIRjeA0AAAAAQDiG1wAAAAAAhHPu6Oho2u8BAAAAAAAqfPIaAAAAAIBwDK8BAAAAAAjH8BoAAAAAgHAMrwEAAAAACMfwGgAAAACAcAyvAQAAAAAIx/AaAAAAAIBwDK8BAAAAAAjH8BoAAAAAgHAMrwEAAAAACMfwGgAAAACAcAyvAQAAAAAIx/AaAAAAAIBwDK8BAAAAAAjH8BoAAAAAgHAMrwEAAAAACMfwGgAAAACAcAyvAQAAAAAIx/AaAAAAAIBwDK8BAAAAAAjH8BoAAAAAgHAMrwEAAAAACMfwGgAAAACAcAyvAQAAAAAIx/AaAAAAAIBwDK8BAAAAAAjH8BoAAAAAgHAMrwEAAAAACMfwGgAAAACAcP4Pr29sYl9hTa8AAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 1800x1200 with 8 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 1800x1200 with 8 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-0ksgzgxXk1F"
      },
      "source": [
        "# Conditional Image Completion\n",
        "\n",
        "Let's let ImageGPT complete the rest! For this, we also add the start token. Note that we can leverage all possibilities of HuggingFace's generate() method, which are explained in detail in [this blog post](https://huggingface.co/blog/how-to-generate)."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ySPBUloCXw3p",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "8f7c834d-5783-4abe-e5c2-9750a6a0d7c3"
      },
      "source": [
        "context = np.concatenate((np.full((batch_size, 1), model.config.vocab_size - 1), primers), axis=1)\n",
        "context = torch.tensor(context).to(device)\n",
        "output = model.generate(input_ids=context, max_length=n_px*n_px + 1, temperature=1.0, do_sample=True, top_k=40)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EF8FKNJZXw3s",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 205
        },
        "outputId": "c6f8562c-7cf9-4b76-a733-e61a82cba4e5"
      },
      "source": [
        "#visualize samples with Image-GPT color palette. \n",
        "samples = output[:,1:].cpu().detach().numpy()\n",
        "samples_img = [np.reshape(np.rint(127.5 * (clusters[s] + 1.0)), [n_px, n_px, 3]).astype(np.uint8) for s in samples] # convert color cluster tokens back to pixels\n",
        "f, axes = plt.subplots(1, batch_size, dpi=300)\n",
        "\n",
        "for img,ax in zip(samples_img, axes):\n",
        "    ax.axis('off')\n",
        "    ax.imshow(img)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 1800x1200 with 8 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dM28iaIh8NiN"
      },
      "source": [
        "Let's combine them into a single image:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1f4Pq0Cb8NXL",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 81
        },
        "outputId": "dab6bf2a-c4f4-43b6-d2fb-3a81912adb5f"
      },
      "source": [
        "import numpy as np\n",
        "\n",
        "row1 = np.hstack(samples_img[:4])\n",
        "row2 = np.hstack(samples_img[4:])\n",
        "result = np.vstack([row1, row2])\n",
        "\n",
        "Image.fromarray(result)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<PIL.Image.Image image mode=RGB size=128x64 at 0x7F87E0C4A410>"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HsrUCc7yqQFA"
      },
      "source": [
        "## Gradio demo"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Xu0Nlf0yqQ84"
      },
      "source": [
        "!pip install -q gradio"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4z6Ff4jqGOMJ"
      },
      "source": [
        "url = 'https://upload.wikimedia.org/wikipedia/commons/thumb/6/6e/Football_%28soccer_ball%29.svg/1200px-Football_%28soccer_ball%29.svg.png'\n",
        "image = Image.open(requests.get(url, stream=True).raw)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "heVulj8WGROI",
        "outputId": "a9b7a150-163b-4bb0-a267-a4088aa593d5"
      },
      "source": [
        "image"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<PIL.PngImagePlugin.PngImageFile image mode=RGBA size=1200x1275 at 0x7F380FC36A50>"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 991
        },
        "id": "0uz931X6qfyR",
        "outputId": "89335d52-909c-4783-dbbb-42a04baa5b88"
      },
      "source": [
        "import os\n",
        "os.system('pip install git+https://github.com/huggingface/transformers --upgrade')\n",
        "\n",
        "import gradio as gr\n",
        "from transformers import ImageGPTFeatureExtractor, ImageGPTForCausalImageModeling\n",
        "import torch\n",
        "import numpy as np\n",
        "import requests\n",
        "from PIL import Image\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "feature_extractor = ImageGPTFeatureExtractor.from_pretrained(\"openai/imagegpt-medium\")\n",
        "model = ImageGPTForCausalImageModeling.from_pretrained(\"openai/imagegpt-medium\")\n",
        "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
        "model.to(device)\n",
        "\n",
        "# load image examples\n",
        "urls = ['https://avatars.githubusercontent.com/u/326577?v=4',\n",
        "        'https://upload.wikimedia.org/wikipedia/commons/thumb/6/6e/Football_%28soccer_ball%29.svg/1200px-Football_%28soccer_ball%29.svg.png',\n",
        "        'https://i.imgflip.com/4/4t0m5.jpg',\n",
        "        ]\n",
        "for idx, url in enumerate(urls):\n",
        "  image = Image.open(requests.get(url, stream=True).raw)\n",
        "  image.save(f\"image_{idx}.png\")\n",
        "\n",
        "def process_image(image):\n",
        "    # prepare 8 images, shape (8, 1024)\n",
        "    batch_size = 8\n",
        "    encoding = feature_extractor([image for _ in range(batch_size)], return_tensors=\"pt\")\n",
        "    # create primers\n",
        "    samples = encoding.pixel_values.numpy()\n",
        "    n_px = feature_extractor.size\n",
        "    clusters = feature_extractor.clusters\n",
        "    n_px_crop = 16\n",
        "    primers = samples.reshape(-1,n_px*n_px)[:,:n_px_crop*n_px] # crop top n_px_crop rows. These will be the conditioning tokens\n",
        "    \n",
        "    # generate (no beam search)\n",
        "    context = np.concatenate((np.full((batch_size, 1), model.config.vocab_size - 1), primers), axis=1)\n",
        "    context = torch.tensor(context).to(device)\n",
        "    output = model.generate(input_ids=context, max_length=n_px*n_px + 1, temperature=1.0, do_sample=True, top_k=40)\n",
        "    # decode back to images (convert color cluster tokens back to pixels)\n",
        "    samples = output[:,1:].cpu().detach().numpy()\n",
        "    samples_img = [np.reshape(np.rint(127.5 * (clusters[s] + 1.0)), [n_px, n_px, 3]).astype(np.uint8) for s in samples] \n",
        "    \n",
        "    # stack images horizontally\n",
        "    row1 = np.hstack(samples_img[:4])\n",
        "    row2 = np.hstack(samples_img[4:])\n",
        "    result = np.vstack([row1, row2])\n",
        "    \n",
        "    # return as PIL Image\n",
        "    completion = Image.fromarray(result)\n",
        "    return completion\n",
        "\n",
        "title = \"Interactive demo: ImageGPT\"\n",
        "description = \"Demo for OpenAI's ImageGPT: Generative Pretraining from Pixels. To use it, simply upload an image or use the example image below and click 'submit'. Results will show up in a few seconds.\"\n",
        "article = \"<p style='text-align: center'><a href='https://arxiv.org/abs/2109.10282'>ImageGPT: Generative Pretraining from Pixels</a> | <a href='https://openai.com/blog/image-gpt/'>Official blog</a></p>\"\n",
        "examples =[f\"image_{idx}.png\" for idx in range(len(urls))]\n",
        "\n",
        "iface = gr.Interface(fn=process_image, \n",
        "                     inputs=gr.inputs.Image(type=\"pil\"), \n",
        "                     outputs=gr.outputs.Image(type=\"pil\"),\n",
        "                     title=title,\n",
        "                     description=description,\n",
        "                     article=article,\n",
        "                     examples=examples)\n",
        "iface.launch(debug=True)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Colab notebook detected. This cell will run indefinitely so that you can see errors and logs. To turn off, set debug=False in launch().\n",
            "Running on public URL: https://28411.gradio.app\n",
            "\n",
            "This share link will expire in 72 hours. To get longer links, send an email to: support@gradio.app\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "        <iframe\n",
              "            width=\"900\"\n",
              "            height=\"500\"\n",
              "            src=\"https://28411.gradio.app\"\n",
              "            frameborder=\"0\"\n",
              "            allowfullscreen\n",
              "        ></iframe>\n",
              "        "
            ],
            "text/plain": [
              "<IPython.lib.display.IFrame at 0x7f38066f6ed0>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n",
            "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n",
            "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n",
            "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n",
            "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n"
          ]
        },
        {
          "output_type": "error",
          "ename": "KeyboardInterrupt",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-15-a57243eb0809>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     64\u001b[0m                      \u001b[0marticle\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0marticle\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     65\u001b[0m                      examples=examples)\n\u001b[0;32m---> 66\u001b[0;31m \u001b[0miface\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlaunch\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdebug\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/gradio/interface.py\u001b[0m in \u001b[0;36mlaunch\u001b[0;34m(self, inline, inbrowser, share, debug, auth, auth_message, private_endpoint, prevent_thread_lock, show_error)\u001b[0m\n\u001b[1;32m    644\u001b[0m             \u001b[0;32mwhile\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    645\u001b[0m                 \u001b[0msys\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstdout\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mflush\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 646\u001b[0;31m                 \u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msleep\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0.1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    647\u001b[0m         is_in_interactive_mode = bool(\n\u001b[1;32m    648\u001b[0m             getattr(sys, 'ps1', sys.flags.interactive))\n",
            "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fICdyWexljR5"
      },
      "source": [
        "## Verifying code examples\n",
        "\n",
        "Here we verify whether the code examples in the docs of ImageGPT work fine."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WblJ-TFIIydl"
      },
      "source": [
        "from transformers import ImageGPTFeatureExtractor, ImageGPTForCausalImageModeling\n",
        "import torch\n",
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "\n",
        "feature_extractor = ImageGPTFeatureExtractor.from_pretrained('openai/imagegpt-small')\n",
        "model = ImageGPTForCausalImageModeling.from_pretrained('openai/imagegpt-small')\n",
        "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
        "model.to(device)\n",
        "\n",
        "# unconditional generation of 8 images\n",
        "batch_size = 8\n",
        "context = torch.full((batch_size, 1), model.config.vocab_size - 1) #initialize with SOS token\n",
        "context = torch.tensor(context).to(device)\n",
        "output = model.generate(input_ids=context, max_length=model.config.n_positions + 1, temperature=1.0, do_sample=True, top_k=40)\n",
        "\n",
        "clusters = feature_extractor.clusters\n",
        "n_px = feature_extractor.size\n",
        "\n",
        "samples = output[:,1:].cpu().detach().numpy()\n",
        "samples_img = [np.reshape(np.rint(127.5 * (clusters[s] + 1.0)), [n_px, n_px, 3]).astype(np.uint8) for s in samples] # convert color cluster tokens back to pixels\n",
        "f, axes = plt.subplots(1, batch_size, dpi=300)\n",
        "\n",
        "for img, ax in zip(samples_img, axes):\n",
        "   ax.axis('off')\n",
        "   ax.imshow(img)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nDTWHgN7lksR"
      },
      "source": [
        "from transformers import ImageGPTFeatureExtractor, ImageGPTForImageClassification\n",
        "from PIL import Image\n",
        "import requests\n",
        "\n",
        "url = 'http://images.cocodataset.org/val2017/000000039769.jpg'\n",
        "image = Image.open(requests.get(url, stream=True).raw)\n",
        "\n",
        "feature_extractor = ImageGPTFeatureExtractor.from_pretrained('openai/imagegpt-small')\n",
        "model = ImageGPTForImageClassification.from_pretrained('openai/imagegpt-small')\n",
        "\n",
        "inputs = feature_extractor(images=image, return_tensors=\"pt\")\n",
        "outputs = model(**inputs)\n",
        "logits = outputs.logits"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qDMzpBX4n3Iw"
      },
      "source": [
        "logits.shape"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zgDNcZYloIyR"
      },
      "source": [
        "from transformers import ImageGPTFeatureExtractor, ImageGPTModel\n",
        "from PIL import Image\n",
        "import requests\n",
        "\n",
        "url = 'http://images.cocodataset.org/val2017/000000039769.jpg'\n",
        "image = Image.open(requests.get(url, stream=True).raw)\n",
        "\n",
        "feature_extractor = ImageGPTFeatureExtractor.from_pretrained('openai/imagegpt-small')\n",
        "model = ImageGPTModel.from_pretrained('openai/imagegpt-small')\n",
        "\n",
        "inputs = feature_extractor(images=image, return_tensors=\"pt\")\n",
        "outputs = model(**inputs)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "n_yr1aqF01xj"
      },
      "source": [
        "outputs.last_hidden_state.shape"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "30fgI0TxUFkd"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}